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  • 1.
    Kyösti, Petter
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre.
    Lindström, John
    Dielcon AB, 954 41 S Sunderbyn, Sweden.
    SOA-Based Platform Use in Development and Operation of Automation Solutions: Challenges, Opportunities, and Supporting Pillars towards Emerging Trends2022In: Applied Sciences, E-ISSN 2076-3417, Vol. 12, no 3, article id 1074Article in journal (Refereed)
    Abstract [en]

    The paper which is based on a literature review combined with a case study, spanning manufacturing and process industry contexts, set out to determine whether there is an emerging trend to use a service-oriented architecture (SOA)-based platform supporting microservices while developing and operating automation solutions while also considering effects and implications. The results point out that there is a significant potential, during the lifecycle, to save significant engineering time/effort during the development-related and operations phases while integrating systems and adding new types of sensors or other equipment. In addition, the results indicate that there are also business development advantages when promoting an SOA-based architecture supporting microservices towards monolith architectures and that a cybersecurity baseline can be included as part of the platform baseline. However, there is a threshold, before the benefits can be reaped, in terms of the need to build up a competency and skills set concerning the platform, SOA and microservices, as many providers of automation solutions are still doing the development in a traditional old monolithic style with hard-coded integrations between components and systems. Finally, we see an emerging trend to use a competent SOA-based platform in the development and operation of automation solutions.

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  • 2.
    Källström, Elisabeth
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development. Volvo Construction Equipment, Eskilstuna, SE-63185, Sweden.
    Lindström, John
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre.
    Håkansson, Lars
    Department of Applied Signal Processing, Blekinge Institute of Technology, Karlskrona, 371 79, Sweden.
    Karlberg, Magnus
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Öberg, Olof
    Volvo Construction Equipment, Eskilstuna, SE-63185, Sweden.
    Renderstedt, Reza
    Volvo Construction Equipment, Eskilstuna, SE-63185, Sweden.
    Larsson, Jonas
    Volvo Construction Equipment, Eskilstuna, SE-63185, Sweden.
    Identification of vibration properties of heavy duty machine driveline parts as a base for adequate condition monitoring: Torque converter2016In: ICSV 2016 - 23rd International Congress on Sound and Vibration: From Ancient to Modern Acoustics / [ed] Vogiatzis, K; Kouroussis, G; Crocker, M; Pawelczyk, M, 2016Conference paper (Refereed)
    Abstract [en]

    Improving uptime is paramount in the heavy duty construction equipment business. Failure ofcritical components in the heavy duty machine may lead to unnecessary stops and expensive downtime. The torque converter, a complex omponent of the driveline, transmits and multiplies torque from the engine to the gearbox, and its failure may not only lead to the machine standing still but may also lead to damage of other parts of the automatic transmission. For adequate condition monitoring of the torque converter, different sensor data are measured on a construction equipment machine during controlled driving sessions. Vibration has been measured on the torque converter. An initial investigation of the vibration measured on the torque converter has been carried out to identify its vibration properties in order to enable its health monitoring to prevent failure. Initial signal analysis of the data have been carried out using Order Power Spectrum and Order Modulation Spectrum methods. The results indicate that the torque converter vibration properties contain information relevant for early fault detection.

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    fulltext
  • 3.
    Lejon, Erik
    et al.
    Gestamp HardTech AB.
    Kyösti, Petter
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre.
    Lindström, John
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre.
    Machine learning for detection of anomalies in press-hardening: Selection of efficient methods2018In: Procedia CIRP, E-ISSN 2212-8271, Vol. 72, p. 1079-1083Article in journal (Refereed)
    Abstract [en]

    The paper addresses machine learning methods, utilizing data from industrial control systems, that are suitable for detecting anomalies in the press-hardening process of automotive components. The paper is based on a survey of methods for anomaly detection in various applications. Suitable methods for the press-hardening process are implemented and evaluated. The result shows that it is possible to implement machine learning for anomaly detection by non-machine learning experts utilizing readily available programming libraries/APIs. The three evaluated methods for anomaly detection in the press-hardening process all perform well, with the autoencoder neural network scoring highest in the evaluation.

  • 4.
    Lindström, John
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Digitalisering för företag inom tillverknings- och processindustrin: Visionärt kunskapsunderlag till den regionala digitala agendan2016Report (Other academic)
    Download full text (pdf)
    fulltext
  • 5.
    Lindström, John
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre.
    Extending the Functional Products definition with additional through-life-cycle aspects2016In: International Journal of Product Development, ISSN 1477-9056, E-ISSN 1741-8178, Vol. 21, no 4, p. 288-329Article in journal (Refereed)
    Abstract [en]

    The paper provides a comprehensive overview on which through-life cycle aspects of Functional Products (FP) are relevant to consider during development and later operation until end of life. The aspects, which are already proposed as part of the current definition of FP, are corroborated, and the additional new aspects found are proposed to extend the current definition of FP. An additional eight new aspects have been found, spanning, e.g., asset management, business model and research collaboration. Some of these new aspects may be relevant for the concepts of servitisation, through-life engineering services, product-service systems and industrial product-service systems as well. The practical implications of the results are that FP customers can improve their reasoning and requirement engineering together with FP providers. FP providers can, on the other hand, use the results to improve their long-term planning and activities from initial development activities (i.e. business case and requirement engineering) to operation at customer sites. The theoretical implications are that the additional new aspects and the proposed extended FP definition provide a foundation for researchers as well as indicating aspects/areas to further explore.

  • 6.
    Lindström, John
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Eliasson, Jens
    ThingWave AB, 954 32 Gammelstad, Sweden.
    Hermansson, Anders
    BnearIT AB, 972 34 Luleå, Sweden.
    Blomstedt, Fredrik
    BnearIT AB, 972 34 Luleå, Sweden.
    Kyösti, Petter
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Cybersecurity level in IPS2: A case study of two industrial internet-based SME offerings2018In: Procedia CIRP, E-ISSN 2212-8271, Vol. 73, p. 222-227Article in journal (Refereed)
    Abstract [en]

    In a case study comprising two SMEs offering Industrial Product-Service Systems (IPS2) based on the industrial internet the paper addresses the current cybersecurity level of the two SMEs and the perceived need for added cybersecurity features. Cybersecurity is of crucial importance for most IPS2-offerings if they involve data communications, data collection and storage, and are also part of the customers’ critical processes (i.e., the core processes that always need to work with a high level of availability). The case study reveals that both IPS2-offerings have a basic level of core security spanning IoT-devices, IoT-networks, cloud services and users as well as administrators. Further, of interest is that the SMEs would like to add security cloud services with advanced security functionality in order to achieve scalability and efficiency regarding security- and general management as well as lifecycle management functionality. However, most of the security cloud services are mainly aimed at larger companies and not adapted for SMEs in terms of required knowledge, time and effort required to keep the security configurations up-to-date.

  • 7.
    Lindström, John
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre.
    Kyösti, Petter
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre.
    Delsing, Jerker
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Ventä, Olli (Contributor)
    Savolainen, Jouni (Contributor)
    Kangas, Petteri (Contributor)
    Helaakoski, Heli (Contributor)
    Virkkunen, Riikka (Contributor)
    Muhos, Matti (Contributor)
    Taipale-Erävala, Kyllikki (Contributor)
    Parida, Vinit (Contributor)
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
    Sjödin, David (Contributor)
    Luleå University of Technology, Centre for Management of Innovation and Technology in Process Industry, Promote. Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
    European roadmap for industrial process automation2018Report (Other academic)
    Abstract [en]

    This is an updated version of the ProcessIT. EU roadmap for industrial process automation, which was initially released in 2013 to provide guidance and input for process industry companies, providers of process industrial IT- and automation solutions, researchers as well as policy makers and bodies/initiatives that craft calls for RDI-projects. The main objective is for European process industry to stay competitive, profitable and sustainable. Thus, to support European process industry in its industrial process automation endeavours, the ProcessIT. EU roadmap outlines three top-level needs: sustainable production, competence management and trust, security, safety and privacy. These three top-level needs intersect the following ten R&D areas:

    • Productivity, efficiency, scalability and flexibility

    • Sustainability through circular economy - circular economy through industrial internet

    • Distributed production/modular factories and services

    • Artificial Intelligence and Big Data

    • Autonomous plants and remote operations

    • Platform economy

    • Cybersecurity

    • Safety - human, machine and environment

    • Competences and quality of work

    • Human-Machine Interfaces and Machine- to-Machine communications,

    which in turn are used as building blocks in the nine gamechangers . The gamechangers aim to influence the process industries’ competitiveness, profitability and sustainability . The gamechangers are listed below:

    • Modular factory for distributed and automated production

    • Live virtual twins of raw-materials, process and products

    • Increased information transparency between field and ERP

    • Real-time data analytics

    • Dynamic control and optimisation of output tolerances

    • Process industry as an integrated and agile part of the energy system

    • Management of critical knowledge

    • Semi-autonomous automation engineering

    • Integrated operational and cybersecurity management

    Finally, the ProcessIT. EU roadmap provides an insight into what may need to be considered on strategic and tactical levels, in terms of: objec-tives, R&D areas, game changers and business modelling, to keep and develop the competitive edge and initiative.

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    fulltext
  • 8.
    Nikolakopoulos, George
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Gustafsson, Thomas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Martinsson, Pär-Erik
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, ProcessIT Innovations R&D Centre.
    Andersson, Ulf
    Mine Tek HB, Kiruna, Sweden.
    A Vision of Zero Entry Production Areas in Mines2015In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 48, no 17, p. 66-68Article in journal (Refereed)
    Abstract [en]

    This industrial article aims in presenting a short roadmap on the identified activities and technologies needed towards the vision of zero entry production areas in Mines. This work has been performed in close cooperation with large mining companies in Europe as part of the Smart Mine of the Future Research, Development and Innovation Program and will present the most important areas that it is expected the robotic technology to have an impact on.

1 - 8 of 8
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